Computer X-ray tomography (CT) is a 3D viewing technique for the diagnosis of internal diseases. FIG. 1 shows an example of a prior art CT system 100. The system includes an X-ray source 105 and an array of X-ray detectors 110. In CT, the X-Ray source is rotated around a subject 115 by a CT scanner. The X-ray source 105 projects radiation through the subject 115 onto the detectors 110 to collect projection data. The subject 115 may be placed on a movable platform 120 that is manipulated by a motor 125 and computing equipment 130. This allows the different images to be taken at different locations. The collected projection data is then transferred to the computing equipment 130. A 3D image is then reconstructed mathematically from the rotational X-ray projection data using tomographic reconstruction. The 3D image can then be viewed on the video display 135.
Magnetic Resonance Imaging (MRI) is a diagnostic 3D viewing technique where the subject is placed in a powerful uniform magnetic field. In order to image different sections of the subject, three orthogonal magnetic gradients are applied in this uniform magnetic field. Radio frequency (RF) pulses are applied to a specific section to cause hydrogen atoms in the section to absorb the RF energy and begin resonating. The location of these sections is determined by the strength of the different gradients and the frequency of the RF pulse. After the RF pulse has been delivered, the hydrogen atoms stop resonating, release the absorbed energy, and become realigned to the uniform magnetic field. The released energy can be detected as an RF pulse. Because the detected RF pulse signal depends on specific properties of tissue in a section, MRI is able to measure and reconstruct a 3D image of the subject. This 3D image or volume consists of volume elements, or voxels.
Imaging in MRI and CT is complicated by image noise in the resulting reconstructed images. There are several sources of noise in MRI. Examples of noise sources include electronic thermal noise in the MRI detectors and noise caused by Brownian motion of ions in bodily fluids of the patient. In CT, noise, resolution, and radiation dose are closely related. Noise is primarily determined by the total amount of information (i.e. radiation) that reaches the detectors after being attenuated by the patient. The uncertainty per voxel (the noise) will be higher if the resolution is increased while keeping the radiation dose constant. Likewise, the uncertainty per voxel will also increase if the radiation dose is lowered or if there is a higher attenuation of the X-ray beams. While increasing radiation dose improves image quality, lowering the dose decreases the risk of possible harmful side effects in patients from ionizing radiation. The diagnostic capabilities of CT can be increased by decreasing noise on and around important internal structures while preserving the spatial resolution of the structures. Maintaining the spatial resolution during noise filtering results making smaller details easier to distinguish, thereby improving diagnosis.
All methods of spatial filtering of 3D images typically involve some type of trade off between computational speed and image quality. Currently, filtering methods that give the best results in image quality are those that use algorithms that are computationally complex and are not regarded as useful in clinical applications.